Towards Reactive Robotics with a Pinch of Image-Schematic Reasoning

Today’s robots do not possess a deep understanding of interactions between physical objects that is also available to their behavior generation modules and as such show brittle performance in realistic environments. While this suggests a robot would therefore need more knowledge, its decisions should not
be too complicated to arrive at or else the robot risks losing track of what matters from its environment. Thus, we investigate a mix of reactive approaches to robotics and reasoning, and propose a simplified theory of typical changes between image schemas. We show how this theory could be integrated in a robot’s perception-action loop, and describe some examples of using this theory to infer actions and perception queries for various stages of a pouring task. We are integrating this inference procedure into a simulated robot, but this integration is yet to be completed and as such, future work.